sprm (1.2.2)

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Sparse and Non-Sparse Partial Robust M Regression and Classification.

http://cran.r-project.org/web/packages/sprm

Robust dimension reduction methods for regression and discriminant analysis are implemented that yield estimates with a partial least squares alike interpretability. Partial robust M regression (PRM) is robust to both vertical outliers and leverage points. Sparse partial robust M regression (SPRM) is a related robust method with sparse coefficient estimate, and therefore with intrinsic variable selection. For binary classification related discriminant methods are PRM-DA and SPRM-DA.

Maintainer: Irene Hoffmann
Author(s): Sven Serneels (BASF Corp) and Irene Hoffmann

License: GPL (>= 3)

Uses: cvTools, ggplot2, pcaPP, reshape2, robustbase

Released over 3 years ago.


3 previous versions

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